THESIS
2016
Abstract
Numerous encrypted database management systems (EDBMSs) were recently developed
to address data confidentiality in case the database server is compromised. Data
is encrypted before it is stored at a server and the private keys are kept away from
the server. The challenge in the EDBMS development is that the server is not able to
perform usual database operations on the encrypted data. Novel techniques were proposed
to address this issue, but most studies focused on facilitating query processing
in EDBMS while little attention was paid on indexing. A secure and effective indexing
method for EDBMS has not been seen. In this paper, we develop an indexing mechanism
called past results knowledge base (PRKB) for EDBMS. Unlike any traditional
indexing method where the index is built o...[
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Numerous encrypted database management systems (EDBMSs) were recently developed
to address data confidentiality in case the database server is compromised. Data
is encrypted before it is stored at a server and the private keys are kept away from
the server. The challenge in the EDBMS development is that the server is not able to
perform usual database operations on the encrypted data. Novel techniques were proposed
to address this issue, but most studies focused on facilitating query processing
in EDBMS while little attention was paid on indexing. A secure and effective indexing
method for EDBMS has not been seen. In this paper, we develop an indexing mechanism
called past results knowledge base (PRKB) for EDBMS. Unlike any traditional
indexing method where the index is built on plain data, we extract and accumulate
knowledge from range query results to form PRKB. PRKB is secure since it does not
leak additional information to an attacker. EDBMS can use PRKB to boost the performance
of range query processing. In our empirical studies, PRKB can reduce query
processing cost by orders of magnitudes compared to the case that no indexing is used.
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